基于可拓熵理论的泥石流危险性评价

评价泥石流危险性的方法有很多,但是各有局限,需要探究危险性评价新方法。利用可拓学原理构建一组能够描述泥石流危险性评价指标的物元模型,采用熵理论计算物元模型中各评价指标的权重值,建立基于可拓熵理论的泥石流危险性评价模型,并通过Visual Basic开发一个基于该模型的泥石流危险性评价软件。选取云南省东川地区12条典型泥石流沟作为检验对象,基于可拓熵理论的评价方法对各沟危险性评价的结果与现有资料完全吻合,从而验证该方法的有效性;进一步以危险评价模型对美姑河柳洪沟流域进行泥石流危险性评价,评价结果同样与现场勘察情况相一致。评价结果表明,基于可拓熵理论的模型能准确地评价泥石流危险等级,开发软件大大减少评价的工作量。     

基于纹理分水岭的斜坡单元提取算法

斜坡单元在以滑坡为主的地质灾害预防和评价中有着广泛的应用，其提取和划分是滑坡灾害风险评估的首要工作和重要基础。针对传统地理信息系统（GIS）方法提取的斜坡单元存在平行边界和误分割问题，提出了基于纹理分水岭的斜坡单元提取方法，通过分割地形图像划分斜坡单元。首先通过预处理地形数据得到数字高程模型（DEM）图像，利用灰度共生矩阵提取DEM纹理特征；然后计算融合灰度和纹理特征的梯度图像，对梯度图像进行基于标记的分水岭分割，使其能够准确获取山体和流域边界；最后，结合正负地形，对山体对象进行分水岭分割以实现斜坡单元的提取。实验结果表明，所提方法对不同地貌类型和分辨率的DEM图像都有良好的划分效果；相较于传统的GIS方法，该方法能够正确分割水平面和倾斜面，有效避免因洼地填平处理而产生的平行边界问题。     

空间信息支持下的江西定南稀土矿区泥石流危险性评价

江西省定南县是我国离子型稀土矿的主要产区。在稀土开采的同时,产生了大量水土流失,诱发的多处泥石流淹没林地和耕地。运用QuickBird高分辨率遥感信息与3D可视化技术相结合对定南矿区开采面、固体废弃物及其造成的泥石流进行解译,根据泥石流分布特点选取危险性评价因子,建立了评价模型,依据预测结果划分了泥石流的危险性空间分布。预测结果得到遥感影像和野外实际调查的检验,模型在赣南离子型稀土矿区有一定的推广意义。     

遗传BP神经网络在泥石流危险性评价中的应用

泥石流危险性的评价是地质灾害预测的重要研究课题之一,根据泥石流危险性评价因子,建立了遗传BP神经网络评价模型。模型利用BP神经网络的函数逼近能力,模拟泥石流某些主要评价指标与危险程度之间的非线性函数关系,实现对泥石流危险性的评价。为克服BP神经网络收敛慢、易陷入局部极小、泛化能力差等缺陷,引入遗传算法和对比分析方法优化BP评价网络的权值、阈值和网络结构。实验证明,采用所述方法优化后的BP神经网络的拟合精度、准确度、效率大幅提高,泛化能力也得到增强,该方法可作为解决泥石流危险性评价问题的一种新思路。     

基于径向基函数神经网络的泥石流危险性评价*

泥石流危险性的主要评价指标与危险程度之间有着某种复杂的非线性的关系,通常采用统计分析、模糊评价、BP神经网络等评价方法,但这些方法均存在不足之处,难以进行准确评价。为了克服以上方法的不足,结合泥石流危险性评价指标,建立了基于径向基函数神经网络的泥石流危险性评价模型,并将该模型结果与BP神经网络的评价结果进行了对比。实验结果表明,径向基函数神经网络的模拟结果比BP神经网络更接近测量数据,精度更高,训练所需时间更少。因此,径向基函数神经网络经过充分训练后,能够较为准确地对泥石流的危险性进行评价,具有较好的应用     

基于GIS和神经网络的泥石流危险性评价系统

基于ArcEngine组件和．Net集成开发天山公路泥石流危险性评价系统,将GIS技术和神经网络集成应用于泥石流危险性评价中,发挥GIS强大的空间信息可视化管理和分析功能以及神经网络的非线性描述和分析功能,实现泥石流危险性评价的可视化管理,为工程决策者和管理人员提供一种强有力的决策支持方案。     

泥石流危险性分区仿真系统的研究与实现

研究泥石流灾害防治问题,为深入分析揭示泥石流运动规律和再现泥石流爆发过程,提高泥石流灾害防治能力,以计算机仿真技术为手段,GIS技术和流团模型为基础,通过用户提供的地形数据,根据数学模型对泥石流运动进行仿真,得出泥石流运动过程中的运动参数,利用GIS技术进行处理、分析,获得泥石流运动范围内各处的相关信息,实现了危险性分区的可视化识别.仿真结果表明,为险情预报和抢险救灾提供依据和指导.系统应用在云南蒋家沟泥石流流域中,得到了较好的仿真效果,可为实际应用提供依据.     

基于水土耦合的泥石流预报系统设计与实现

为提高泥石流业务预报的准确性，满足泥石流减灾的需求，运用GIS技术，设计并实现基于流域水土耦合机制的区域泥石流预报系统。通过分布式水文模型和非饱和土极限平衡法实时评估每条泥石流流域内的水土混合物密度ρ，利用ρ判定区域内每条泥石流流域内发生泥石流概率的大小，实时发布泥石流预警信息。以四川省为研究区，以2013年7月9日特大降雨过程诱发大规模泥石流灾害事件作为系统的验证实例。验证结果表明，该系统运行稳定且具有较高的预报精度，能够很好地满足泥石流减灾需求。     

基于GIS的泥石流流域分布式水文计算系统

基于GIS技术与分布式水文模型,设计并实现泥石流流域分布式水文计算系统。以流域降雨、高程、坡度等数据为输入,对泥石流流域的降雨产流、产沙进行模拟,自动批量计算指定时间段内每日流域出口清水流量、泥沙流量以及流水含沙量。将系统应用到云南蒋家沟泥石流流域中,计算得到的高含沙水流含沙量与实测的含沙量数据误差很小,表明系统具有较高的精度和适用性。     

基于GIS的泥石流流域分布式水文计算系统

基于GIS技术与分布式水文模型,设计并实现泥石流流域分布式水文计算系统。以流域降雨、高程、坡度等数据为输入,对泥石流流域的降雨产流、产沙进行模拟,自动批量计算指定时间段内每日流域出口清水流量、泥沙流量以及流水含沙量。将系统应用到云南蒋家沟泥石流流域中,计算得到的高含沙水流含沙量与实测的含沙量数据误差很小,表明系统具有较高的精度和适用性。     

基于伪卫星测试的并行计算灾害救援中心选定模型构建

泥石流具有时间和空间群发性、运动持续性、灾害链式性、类型单一性、致灾方式和受灾对象的多样性特点;灾害救援中心位置选取过程是典型的非线性不收敛问题;单纯以线性技术和约束条件为基础的模型面对复杂泥石流灾害指标的情况下,会出现较大偏差;提出基于伪卫星测试结合并行计算的灾害救援中心选定模型设计方法;以泥石流灾害为例,利用离散元法和GPU并行算法构建泥石流运动堆积模型,将沟道泥石流汇流后运动堆积特点和灾害区域当作模拟参照,对泥石流运动进行模拟,根据模拟结果,预测泥石流覆盖范围;利用伪卫星技术计算灾害扩散程度和易发点距离,在救援中心搭建费用与救援成本最低前提下,将用户选择的位置与高度作为已知条件,以期望损失最低为约束,以精度因子为标准得到救援选址的核心区域点,构建基于伪卫星测试的灾害救援中心选定模型;仿真实验表明,设计模型的选址精度和效率较高,可为泥石流灾害救援提供数据支撑。     

Estimation of stream channel geometry in Idaho using GIS-derived watershed characteristics

This paper describes estimation of stream channel geometry with multiple regression analysis of GIS-derived watershed characteristics including drainage area, catchment-averaged precipitation, mean watershed slope, elevation, forest cover, percent area with slopes greater than 30 percent, and percent area with north-facing slopes greater than 30 percent. Results from this multivariate predictor method were compared to results from the traditional single-variable (drainage area) relationship for a sample of 98 unregulated and undiverted streams in Idaho. Root-mean-squared error (RMSE) was calculated for both multiple- and single-variable predictions for 100 independent, random subsamples of the dataset at each of four different subsample levels. The multiple-variable technique produced significantly lower RMSE for prediction of both stream width and depth when compared to the drainage area-only technique. In the best predictive equation, stream width depended positively on drainage area and mean watershed precipitation, and negatively on fraction of watershed consisting of north-facing slopes greater than 30%. Stream depth depended positively on drainage area and precipitation, and negatively on mean watershed elevation. Our results suggest that within a given physiographic province, multivariate analysis of readily available GIS-derived watershed variables can significantly improve estimates of stream width and depth for use in flow-routing software models.     

Regional assessment of geohazard recovery eight years after the Mw7.9 Wenchuan earthquake: a remote-sensing investigation of the Beichuan region

The earthquake of 12 May 2008 in Wenchuan County, Sichuan Province, China, devastated the entire Beichuan region. Sitting at the intersection of the Yingxiu-Beichuan and Pengguan faults, the region experienced seismic intensities of VIII–XI on the Liedu scale. High seismic intensity combined with inherent geomorphological and climatic susceptibility to slope failure resulted in widespread co-seismic geohazards (slope failures of various types), which decimated the region. The seismic characteristics of the Wenchuan earthquake and the co-seismic geohazard distribution in relation to various conditioning factors have previously been examined in depth. However, there has been a lack of regional assessment of temporal and spatial recovery from co-seismic geohazards. Triggered by the authors’ field observation of rapid recovery, this study presents a temporal series of geohazard maps, produced by manual interpretation of satellite imagery, to present an initial assessment of changes in geohazard occurrence in the Beichuan region since the Wenchuan earthquake. In particular, landscape recovery at the co-seismic geohazard sites, as indicated by re-vegetation, is analysed based on temporal/spatial characteristics of geohazard distribution, in relation to co-seismic deformation, distance from the rupture zone and slope angle. Eight years after the Wenchuan earthquake, the overall recovery stands at 65.48%, with approximately uniform annual rates of recovery at 13.45% a year between 2009 and 2011 and 10.56% a year between 2012 and 2016. Whilst co-seismic geohazards are concentrated on the hanging wall of the seismic fault, landscape recovery is more significant in the very highly deformed zone than in other areas. Recovery has been the greatest on slopes of <50^° and peaks on 40^°–50^° slopes, where the area occupied by co-seismic geohazards was the largest. The block-slides and rock topples, which characterize high angle slopes, show much slower recovery, possibly due to greater instability and the lack of soil to support re-vegetation.     

基于松鼠觅食算法优化LSSVM的泥石流预测

针对山区村镇泥石流影响因素多元复杂、LSSVM算法参数随机导致的精度不佳及陷入局部最优问题,采用核主成分分析KPCA降维、SSA算法参数寻优的方法建立LSSVM泥石流灾害预测模型。以山阳县中村镇泥石流为例,分析泥石流全域地形地貌成灾因子,对数据预处理清洗规范,利用KPCA主成分贡献率选取出6个成灾因子作为LSSVM算法的输入数据,泥石流发生概率为输出,建立泥石流预报模型,并用SSA算法进行模型参数的优化。将SSA寻优后的LSSVM预测结果与GA、GC参数寻优模型预测结果比对,结果表明SSA-LSSVM准确率达到93.2%,相比其他模型提高[4.8%-1.4%],且SSA算法优化的LSSVM模型的MAE、MSE和RMSE最小且接近于零,同时从泥石流发生的预报等级维度进行结果比对分析,结果进一步说明模型预测的精度及稳健性。本研究说明SSA-LSSVM算法可用于泥石流灾害发生概率的预测,为此类灾害预测提供了科学依据。     

Synergistic approach for mapping debris-covered glaciers using optical-thermal remote sensing data with inputs from geomorphometric parameters

Debris cover on glacier boundaries critically impedes the global inventorying of glaciers and confounds most of the techniques developed for semi-automated mapping of glaciers. Debris on the glacier (referred as supraglacial debris) and that occurring outside the glacier boundaries (referred as periglacial debris) being derived from a common source, i.e. the valley rock, tend to have a similar spectral response in the reflection region which renders them mutually indistinguishable. However, there exist temperature differences between them. This aspect has been considered in this remote sensing based study to distinguish between the supraglacial and periglacial debris in a test area in the Chenab basin, Himalayas, by inclusion of thermal infrared (TIR) bands in remote sensing data processing. A synergistic multisensor approach for the delineation of debris-covered glacier boundaries is used here which integrates the inputs from thermal (TERRA-ASTER sensor) and optical (IRS-P6-AWiFS sensor) remote sensing data, multispectral classification techniques and the DEM derived geomorphometric parameters. The results of this study corroborate earlier findings on utilization of temperature differences as one of the parameters in glacial studies. The proposed synergistic approach therefore appears useful in accurate mapping of debris-covered glaciers in the Himalayan region.     

Quantifying the spatial distribution of soil mass wasting processes after the 2008 earthquake in Wenchuan, China: A case study of the Longmenshan area

The beautiful Longmenshan area is one of the main tourist attractions in Sichuan Province, China. The epicenter of a catastrophic earthquake measured at 8.0 Ms (China Seismological Bureau), occurred within this area at Wenchuan (31°01′16″N, 103°22′01″E) at 14:28 May 12, 2008 (Beijing time). The earthquake triggered numerous types of landslide transport and hazards, including soil and debris avalanches, rockfalls, slumps, debris flows, creation of barrier lakes and slope flattenings. This paper examines the landslide hazards in the Longmenshan area caused by the earthquake using remotely sensed images, mainly Beijing-1 Microsatellite data before and after the earthquake, compared to digital elevation maps and slope gradient maps, land use and vegetation cover maps. Areas of erosion and loss of vegetation were compared from pre- and post-earthquake data, from which were calculated changes in vegetated areas, bare slopes, and mass movement during the earthquake. These events occurred over altitudes from 1000 to 4000 m and on slope angles between 25 and 55°. The results show that the total area of erosion and land movement due to the earthquake increased by 86.3 km² (19.2% of the study area). Compared with pre-earthquake, the areas of very low intensity soil erosion and moderate intensity soil erosion were respectively reduced by 3.6 km², 24.3 km² and 30.9 km². On the other hand, the areas of severe and very severe intensity soil erosion were substantially increased by 45.8 km² and 99.2 km². In the post-earthquake stage, the bare areas (vegetation cover < 15%) have increased by 65.8 km². Without vegetation, the denuded earthquake damaged slopes and other high risk sites have become severe erosion problems. Thus, it is essential to continue long-term monitoring of mass wasting in the denuded areas and evaluate potential risk sites for future landslides and debris flows. We anticipate that these results will be helpful in decision making and policy planning for recovery and reconstruction in the earthquake-affected area.